Data Scientist

**Responsibilities**:
**Data Analysis and Modelling**:

- Develop and deploy machine learning and artificial intelligence models and algorithms to extract insights, predict outcomes, and optimize processes
- Conduct in-depth data analysis, data exploration, and data preprocessing to extract valuable information from large datasets

**Data Strategy and Planning**:

- Collaborate with stakeholders to define data-driven objectives and formulate data strategies aligned with business goals
- Identify key performance indicators (KPIs) and establish data collection and measurement protocols

**Feature Engineering**:

- Engineer features and create data pipelines to prepare and clean data for modelling
- Work with data engineering teams to ensure data availability and quality

**Model Evaluation and Deployment**:

- Evaluate model performance and fine-tune models for improved accuracy
- Deploy models in production environments and monitor their ongoing performance
- Implement best practices for model version control and management
- Ensure proven models are integrated into business processes and software products removing the requirement for human intervention to implement the model within their respective businesses

**Cross-Functional Collaboration**:

- Collaborate with business analysts, data engineers, and domain experts to understand and address specific business problems
- Communicate findings and insights to non-technical stakeholders in a clear and actionable manner

**Leadership and Mentorship**:

- Provide leadership and mentorship to junior data scientists
- Participate in knowledge-sharing and training programs to enhance the data science capabilities of the team
- Foster a collaborative and innovative work environment

**Data Privacy and Compliance**:

- Ensure data privacy and compliance with relevant regulations and best practices
- Develop and enforce data security protocols

**Requirements**:

- Degree in Computer Science, Data Science, or a related field
- Proven experience in data science roles, including hands-on experience with machine learning, deep learning, and statistical analysis
- Proficiency in data analysis and machine learning tools and libraries e.g. Python, R
- Strong programming skills and knowledge of data manipulation and visualization
- Expertise in data preprocessing, feature engineering, and model evaluation
- Excellent problem-solving and critical-thinking skills
- Strong communication and interpersonal skills to effectively collaborate with various stakeholders
- Relevant certifications e.g. Certified Data Scientist etc. are a plus
- For more information please contact:
**Micaela Naidoo